Three ways to monetise platform business models

The inability to monetise a platform business model will ultimately lead to failure.

Shares

Research shows that by the end of 2020, now less than 12 months away, a quarter of the global economy will be driven by platform businesses. Moreover, 81 per cent of senior executives say that platform-based business models will be core to their growth over the next three years. It is clear that traditional businesses are looking to learn from their disruptive counterparts. However, one thing is clear the inability to monetise a platform business model will ultimately lead to failure. Consequently understanding how to generate revenue from the platform is crucial.

One of the major advantages of a brand creating a platform is the ongoing stream of customer data that it generates. By requiring customers to create an account (i.e. a sign-in) to access their platform, brands can build and refine users’ profiles. These platform profiles become increasingly more sophisticated and targetable over time, as more user behaviour is observed, collected and analysed.

The road to monetisation all starts with the sign-in. Most platforms limit content or functionality whenever a person interacts with the brand anonymously, meaning, the individual hasn’t created a platform account or has failed to sign-in. If you’ve ever tried to view someone’s Facebook profile while forgetting to log in, you likely noticed that you can’t see that person’s entire profile. Rather, Facebook gives you a sampling of information about that person, enough for you to identify whether it’s the person you were looking for, along with a prominent call to action to have you either sign-in or create your own Facebook account. This mechanism is common amongst platform brands since they are always trying to capture new users or connect new data points to existing user profiles. By requiring new users to create a platform profile and returning users to sign-in, platform brands are uniquely positioned to track consumer behaviour across an array of devices. This is notoriously difficult for non-platform brands, i.e. knowing that the person who visited their website from a work computer during the afternoon is the same person who opened their mobile app later that evening. This persistency is perhaps the most valuable aspect of platform sign-ins. Cookies and IDFAs can be cleared, blocked, and are, at best, proof of a returning device, not a returning person. This account sign-in mechanism uniquely creates a persistent data point (or ID) that allows brands to connect a user’s behaviour over time to a profile.

As platform users sign-in via more and more devices, a complete view of this person’s platform experience can be tracked and analysed over time. This gives platform brands near certainty when targeting their users based on some aggregate behavioural trait or other data point, regardless of device. Meanwhile, non-platform brands can, at best, make a probabilistic determination that they are communicating with their intended audience. For consumers, the benefits of having a platform profile are clear, namely convenience. Over time, branded platform users receive a more customised and relevant platform experience that saves them time (no need to enter your credit card number every time you use Uber) or often introduces them to new content or product that they would otherwise be unaware (Amazon, YouTube, etc.)

1. Informed product and content development

For platform brands that sell products or services, there is an immense opportunity to increase sales through the creation of additional content, products, and services that better align with their users’ desires, needs, and lifestyles. By monitoring and analysing their users’ behaviour, whether for content consumption preferences or purchase history, platform brands identify emerging trends that can then be quickly incorporated into product and content development roadmaps before the competition. A great example of this platform brand monetisation approach was Netflix’s 2014 signing of Adam Sandler to an exclusive 4-movie deal. At the time, much of the film industry saw Sandler as a movie star whose fame and box office appeal was on the decline. He had just come off three consecutive films that were considered financially unsuccessful. However, because of their platform, Netflix had audience consumption data that no one else had. Namely, Netflix could see that Sandler movies on their platform had truly global appeal. As Ted Sarandos, Netflix’s Chief Content Officer, put it: “We knew he was popular in markets where his movies had never ever opened.” This insight, stemming from their uniquely owned data, allowed Netflix to confidently offer the 4-picture deal. The results speak from themselves. As of Q1 of 2017, Netflix reported that users have watched 500 million hours of Adam Sandler content since the release of his first Netflix exclusive streaming feature film, The Ridiculous Six, in December 2015.

2. Recommender systems

One of the most common and recognised platform brand monetisation strategies is cross-selling and up-selling to existing users. If a platform brand sells products or services directly, this purchase data can be harnessed to encourage its users (aka customers) to spend more on the platform. However, to do so effectively a brand must understand its customers’ needs, in near real time, to provide relevant recommendations. By applying powerful algorithms to their customer purchase data, platform brands can create a powerful recommender system that drives significant incremental revenue. The best example of this type of platform brand monetisation is, of course, Amazon. For over two decades it has been able to increase cart value by providing its customers with helpful and relevant product recommendations based on their previous purchased and rated items. By now, most everyone is familiar with the ubiquitous but effective “customers who bought this item also bought…” phrase. In fact, Amazon’s recommender system is so effective that they have historically reported that 35 per cent of its revenue comes from these cross-sell and up-sell tactics. It certainly doesn’t hurt that Amazon has arguably the most successful recommendation algorithm in history along with what is likely the largest data set of consumer purchase behaviour in the world.

3. Targeting advertising

No discussion of platform brand data monetisation tactics would be complete without an examination of targeted advertising. Almost all platform brands employ this monetisation approach to some degree, including Amazon, Google, LinkedIn, etc. But what does a platform brand need to successfully implement this revenue model? Foremost, a platform brand must have a large reach to attract national advertisers. If a platform brand only appeals to a niche audience, it will be difficult to scale up ad revenue or appeal to the biggest advertisers. Part of the appeal when advertising on a platform brand is the ability to easily reach large swaths of the target market’s general population, requiring a large audience base. This is why platform brands often take years to implement an ad revenue model and turn a profit. Just take Twitter as one example. The company only began offering paid advertising to brands as mid-2010, four years after the platform’s launch. Even more telling, Twitter has only begun to turn a profit as of this year, relying primarily on ad revenue. However, having a large platform audience is only part of a successful advertising revenue model. To really attract advertising dollars, a platform brand must offer unique audience targeting capabilities to differentiate from other advertising options.

Advertisers increasingly want to be able to accurately address audiences with specific behaviours and interests. Platform brands that drive high user engagement, analyse this data, and connect it to a user/platform profile, are well-positioned to create on-platform advertising that can target granular audience behaviours and interests. Lastly, it is important for platform brands to consider the user experience when implementing a targeted advertising monetisation strategy. The value of any advertising is ultimately judged on its ability to drive action, whether something tangible like a sale or something more conceptual like consideration. To drive their users to take such actions, platform brands must create contextually relevant and non-disruptive ad products. While audience targeting, as described above, is an important piece, the users’ platform experience cannot be overlooked. The reasons people use a brand’s platform must be complimentary to the ad products the brand creates to ensure that the platform’s audiences are in an appropriate mindset for receiving advertisements.

User attention

For example, if Uber were to suddenly show advertisements to its users whenever they tried to hail a car on the go, how receptive would their audience be to an advertiser’s offer? It should be no surprise that Facebook is the prime example of a platform brand implementing advertising as a tactic to monetise their data. First, Facebook has massive reach, with approximately 2.23 billion users globally as of September 2018. While impressive, Facebook does not rely solely on its original social platform. Since their acquisition of Instagram in 2012, the social media giant has clearly implemented an acquisitions strategy to grow and protect its user and profile data across the entire internet. From Oculus to WhatsApp, Facebook has strived to predict and purchase platform brands that threatened to take some of their users’ time and attention. As of March 2018, Facebook owns 3 of the top 10 apps (Instagram, Messenger and Facebook) according to ComScore. In addition, Facebook’s advertising network that launched in 2014 reaches more than one billion people on its own. As discussed, reach alone is insufficient to maximise platform advertising revenue. Platform brands must be able to aggregate and analyse their users’ on-platform behaviour to create addressable audience segments that advertisers can target. As for Facebook’s ability to serve advertisements that are relevant to the target audiences, the proof is in the company’s earnings reports. In 2017, Facebook generated $15.9 billion in earning on a revenue of $40.7 billion, 98 percent of which came from its advertising products and services. Clearly, Facebook has figured out how to effectively serve ads to its users that drive engagement with advertisers and audience action.

Closing comments

Considering the above three tips, it should now be clear why platform models must do everything they can to keep as many people on (and signed into) their platforms, for as long as possible. The more people that engage with and interact on a brand’s platform, the more user data generated and analysed for advertising targeting, product and service recommendations, and platform improvements. When this platform generated data is kept private, as opposed to publicly available, it becomes a competitive advantage. Further, a platform brand that has unique profile data and a large user base can, ultimately, attract advertisers who will pay a premium to access the platform’s audience in a highly targeted and non-disruptive manner.